[1]} used a convolutional neural network for relation extraction. They used the pre-trained word embeddings of [2]} to represent the tokens in a sentence and used two distance embedding vectors to represent the distance of each word from the two entities. They used a convolutional neural network (CNN) and max-pooling operation to extract a sentence-level feature vector. This sentence representation is passed to a feed-forward neural network with a softmax activation layer to classify the relation.
